Nurses’ Perceptions of Climate Change: Protocol for a Scoping Review
Bibliographic record
Abstract
BACKGROUND: Climate change is a major threat to human health. Nurses are in contact with patients suffering from the effects of climate change in their daily work. Therefore, they need to be involved in combating it at both the individual and collective levels. However, there is still very little known about nurses' perception of climate change and their role toward it. A few recent studies have embarked on the process of examining the perceptions of these health professionals relative to climate change, but no exploratory review of the literature has been conducted on nurses' perception of this phenomenon. OBJECTIVE: The purpose of this protocol is to develop a research strategy for an exploratory review of the literature focused on identifying nurses' perceptions of climate change. METHODS: Firstly, with the help of a specialized librarian, we defined keywords and their combinations, using an iterative process, to develop a documentary search strategy. This strategy was tested in the following four bibliographic databases: MEDLINE (PubMed), CINAHL, Embase, and Web of Science. A search of the grey literature will also be conducted to supplement the results of the bibliographic database search. The next step will be for 2 members of the research team to carry out a 2-stage selection process using the web-based systematic review software Covidence. They will carry out this selection process independently, with the aim of identifying relevant studies that meet the inclusion criteria for our exploratory review. Finally, data on year of publication, authors, geographic area, article type, study objectives, methodology, and key findings will be extracted from selected articles for analysis. The data will be analyzed by the research team based on an in-depth examination of the findings and will be directed toward answering the research question and fulfilling the study's objective. RESULTS: The results will help in defining nurses' perceptions of climate change more clearly as well as the role they can play and what they need to be able to bring forward solutions to this phenomenon. The findings should also serve to guide the health sector and nursing faculty's interventions aimed at preparing health professionals to act on the potential threats associated with climate change. CONCLUSIONS: The preliminary search suggests a possible gap between the importance of the nursing role in addressing the health impacts of climate change and the nurses' lack of knowledge and awareness on this matter. The results will allow for raising nurses' awareness of their role in the fight against climate change and the ways to address its health effects. This study will also open up new research perspectives on how to equip nurses to better integrate response to climate change issues into their professional practice. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/42516.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.106 | 0.122 |
| Meta-epidemiology (narrow) | 0.006 | 0.007 |
| Meta-epidemiology (broad) | 0.013 | 0.014 |
| Bibliometrics | 0.016 | 0.014 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.010 | 0.011 |
| Insufficient payload (model declined to judge) | 0.084 | 0.016 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".